1. Field of the Invention
The present invention relates to an image processing apparatus such as a digital printer, digital facsimile apparatus, or the like which deals with an image as a digital signal and to an image processing method which is used in such image processing apparatus. More particularly, the invention relates to an image processing method and apparatus for half-tone processing image data.
2. Related Background Art
In general, digital copying apparatus of a type in which an image is sampled by a CCD sensor or the like, the digitized data is output from a digital printer such as a laser beam printer or the like, and an image is reproduced are used widely in place of a conventional analog copying apparatus, as a result of the development of digital equipment.
Such a digital copying apparatus generally uses a method of reproducing gradations by a dither method or a concentration pattern method in order to reproduce half-tones. However, such methods have drawbacks such as the following:
(1) In the case where an original is a dotted image a result of the use of certain printing methods or the like, a periodic fringe pattern which does not exist in the original appears in the copied image
(2) In the case where an original includes diagrams, characters, and the like, the edges become uneven due to the dither processing, so that the picture quality deteriorates.
The phenomenon of (1) is called a moire phenomenon and occurs by the following causes.
(A) The beats by the dotted original and the input sampling.
(B) The beats by the dotted original and the dither threshold value matrix.
Particularly, in the case of the phenomenon (B), generally, when the threshold values of the dither are arranged in a dot concentration manner, an output image also has a pseudo-dotted structure, causing beats with the input dotted original Thus, the moire phenomenon occurs.
On the other hand, an error diffusion method has been known as a binarization method which has recently been highlighted. According to the error diffusion method, the difference between an image concentration of an original and the output image concentration is calculated for every pixel and the error component as the result of the calculation is diffused by adding special weights to the peripheral pixels. Such a method has been published in the article by R. W. Floyd and L. Steinberg, "An Adaptive Algorithm for Spatial Grey Scale", SID 75 Digest.
On the other hand, a method called a least mean error method has also been known. This method is considered to be substantially equivalent to the error diffusion method.
In the case of binarizing by using such a method, since there is no periodicity in the processing of errors, no moire occurs for the dotted image and the resolution is better than that by the dither method or the like. However, there is a drawback that a unique fringe pattern is generated in the highlight portions of the image. To eliminate the foregoing drawback of the error diffusion method, the assignee of the present invention has already filed U.S. patent application Ser. Nos.: 145,593, 192,601, 203,880, and 284,603, and U.S. Pat No. 4,876,610 and 4,878,125.
On the other hand, according to the error diffusion method, dots are printed on the background of a character portion, causing the deterioration of the picture quality (particularly, in the character portion).
On the other hand, when the error diffusion method is used in a white portion of a low image concentration, the data of low concentrations are gradually accumulated as errors. When the total error amount exceeds a threshold value, the errors appear as a dot, so that the picture quality in the white portion is deteriorated.
The causes of the appearance of the dot will be described with respect to the case where the concentration data is expressed by six bits (0 to 63).
According to the above error diffusion method, for instance, in the case where, for instance, luminance data read by a reading apparatus is digitized into six-bit concentration data 0 (white) to 63 (black) for every pixel and the digitized concentration data is binarized by the error diffusion method, for example, if the data of concentration level "1" is uniformly distributed, the difference between the output data 0 and the concentration data 1 in the case of binarizing the data of the concentration level 1 is sequentially added to the peripheral pixels, so that there is a drawback that when the added pixel value exceeds the threshold value for binarization, a black dot is output.
In other words, in spite of the fact that the portion in which the concentration level 1 is uniformly distributed is seen as a white image on the whole by human eyes, particle-like noises are generated in the white portion because of the occurrence of the black dots. The image quality is deteriorated due to the particle-like noises in the high contrast portion.
On the other hand, even if an entirely white image is read, if the level of the video signal from the CCD is smaller than the dynamic range of an A/D converter, a numerical value of a certain degree is output from the A/D converter even in the case of the whole white portion, so that the particle-like noises are also generated in a manner similar to the foregoing case and the image quality is deteriorated.
On the other hand, in the case where data is binarized and encoded and transmitted as in the case of the facsimile apparatus, particle-like noises (black dots) are generated irrespective of the whole white image, so that there is a drawback such that the encoding efficiency also deteriorates.